The human gut hosts a vast community of microorganisms that can influence our health in many ways, from helping us to digest nutrients to influencing our metabolism, immunity, and even brain function. Because the microbiota can be potentially altered through interventions such as diet or medication, it represents a promising target for improving human health and preventing or treating disease. Yet, despite this potential, we still lack a solid understanding of how specific changes in microbial communities translate into measurable effects on the host metabolism. Each bacterial species carries largely undiscovered metabolic capacities, and can interact with other species by sharing, cross-feeding or competing for nutrients and metabolic by-products. Understanding metabolic abilities of individual microbes and their interaction networks is essential for designing targeted microbiota based interventions.
This project aims to unravel gut microbial interactions through a combination of experimental and computational approaches. Focusing on a synthetic community of ~20 human gut bacteria, we take a bottom up approach to uncover how these microbes transform and trade essential metabolites, including amino acids, vitamins, and compounds that act like hormones. First, we determine which metabolites each bacterial species consumes and produces, and identify the responsible enzymes and pathways. Next, we investigate how these metabolic activities change when bacteria coexist in diverse communities. Finally, we explore how microbial metabolism contributes to the host’s metabolic processes in mouse models. Together, these steps will reveal how individual metabolic traits combine within communities and how these collective activities influence the host.
To achieve this, the project integrates cutting edge methods from several disciplines. We use high throughput bacterial culturing to generate extensive metabolomics and transcriptomics datasets of single species and their synthetic communities, which provide detailed molecular information on microbial responses to metabolic and compositional perturbations. We develop and apply computational tools, such as genome scale metabolic models, graph based multi omics integration methods, and physiology based kinetic simulations of microbiota host interactions, to trace metabolic exchanges from metabolites to microbial genes, to microbes, and ultimately to the host.
By revealing the fundamental principles of how microbial and host metabolic processes interact, this project aims to create a predictive framework that can explain and anticipate how alterations in microbial composition shape the metabolic phenotype of the host. Such knowledge could transform our ability to design targeted microbiota interventions ranging from dietary recommendations and probiotics to precision therapeutics to prevent or treat a wide spectrum of metabolic and systemic diseases. Beyond its immediate findings, the project will deliver generalizable tools and concepts that can be applied to other microbial ecosystems beyond the host environment.
